MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh | Paper Citation Record

Observation 7cc1a323-fdc2-4957-b7c7-6ba0bc66105a · outbound

This paper cites write newline.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh write newline

Reference 1

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Observation 525b7680-d93a-48fa-b3fa-c6f8c562e531 · outbound

This paper cites GPT-4 Technical Report.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh GPT-4 Technical Report

Reference 2

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Observation 35488a98-37bd-455c-bae6-7b2fb5990ca0 · outbound

This paper cites PolyDiff: Generating 3D Polygonal Meshes with Diffusion Models.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh PolyDiff: Generating 3D Polygonal Meshes with Diffusion Models

Reference 3

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Observation d7424d59-7a99-4374-a381-a71cd5f5c2f4 · outbound

This paper cites PaLM 2 Technical Report.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh PaLM 2 Technical Report

Reference 4

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Observation 421f7810-8ce1-411e-95df-9e38d97bee9b · outbound

This paper cites Qwen Technical Report.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Qwen Technical Report

Reference 5

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Observation d96d59c8-dbdc-46ee-8105-39da31456025 · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 6

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Observation 7da8bb43-5e3e-4f4a-bca7-17d14a13c598 · outbound

This paper cites Language models are few-shot learners.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Language models are few-shot learners

Reference 7

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Observation 89ddfee3-6ff2-43e0-ada5-b5aff0e0ea01 · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh ShapeNet: An Information-Rich 3D Model Repository

Reference 8

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Observation 8a8d6e50-1390-48e8-a5df-bc21d9b6295f · outbound

This paper cites Meshxl: Neural coordinate field for generative 3d foundation models.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Meshxl: Neural coordinate field for generative 3d foundation models

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:04.379448Z

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Observation 4b39888c-52b9-46ae-a46b-52c2316118bb · outbound

This paper cites MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T05:46:02.816793Z

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Observation 7f97f44d-ebb9-4832-8075-f73fffb0eea7 · outbound

This paper cites MeshAnything V2: Artist-Created Mesh Generation With Adjacent Mesh Tokenization.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh MeshAnything V2: Artist-Created Mesh Generation With Adjacent Mesh Tokenization

Reference 11

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Observation c0470e3f-7815-476c-9283-cec1e69da632 · outbound

This paper cites Grounded 3D-LLM with Referent Tokens.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Grounded 3D-LLM with Referent Tokens

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T05:46:02.826607Z

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Observation 8ada0358-cb54-45e5-b705-ce5edbf9a8cc · outbound

This paper cites Sdfusion: Multimodal 3d shape completion, reconstruction, and generation.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Sdfusion: Multimodal 3d shape completion, reconstruction, and generation

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:04.361643Z

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Observation 45b2aed7-84ac-41c1-a415-5a5af1d5f385 · outbound

This paper cites Palm: Scaling language modeling with pathways.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Palm: Scaling language modeling with pathways

Reference 14

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Observation 4658863a-3b8c-4d9f-bbe6-d4d7befd8c6f · outbound

This paper cites Scan2mesh: From unstructured range scans to 3d meshes.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Scan2mesh: From unstructured range scans to 3d meshes

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:04.331196Z

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Observation 04352598-a9c7-4709-a878-7c7b146d10a6 · outbound

This paper cites Objaverse-xl: A universe of 10m+ 3d objects.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Objaverse-xl: A universe of 10m+ 3d objects

Reference 16

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Observation 69c233f3-9dfa-4bae-b281-2e80b90b0d1c · outbound

This paper cites Meteor universal: Language specific translation evaluation for any target language.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Meteor universal: Language specific translation evaluation for any target language

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:04.298205Z

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Observation 34b969f0-b45f-4547-a35a-e3369ed91988 · outbound

This paper cites Enhancing Chat Language Models by Scaling High-quality Instructional Conversations.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Enhancing Chat Language Models by Scaling High-quality Instructional Conversations

Reference 18

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Observation 945a12ab-c14c-43d4-87de-a1395576a501 · outbound

This paper cites Hyperdiffusion: Generating implicit neural fields with weight-space diffusion.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Hyperdiffusion: Generating implicit neural fields with weight-space diffusion

Reference 19

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Observation 549dadb8-d8b3-428a-aec9-cdb7c12b1fc1 · outbound

This paper cites Efficient implicit sdf and color reconstruction via shared feature field.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Efficient implicit sdf and color reconstruction via shared feature field

Reference 20

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Observation 2277cddd-96ef-48f1-8d28-ce5996322d1d · outbound

This paper cites Chat-edit-3d: Interactive 3d scene editing via text prompts.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Chat-edit-3d: Interactive 3d scene editing via text prompts

Reference 21

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Observation 2f97c1d0-3845-4053-a2f2-b78ee24c5ffc · outbound

This paper cites Scene-LLM: Extending Language Model for 3D Visual Understanding and Reasoning.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Scene-LLM: Extending Language Model for 3D Visual Understanding and Reasoning

Reference 22

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Observation 25a2f1d4-ac01-4c9f-8039-37dafbf1f5a7 · outbound

This paper cites Worldgpt: Empowering llm as multimodal world model.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Worldgpt: Empowering llm as multimodal world model

Reference 23

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Observation 44ac5512-842a-4007-810e-df96efa84e50 · outbound

This paper cites Imagebind: One embedding space to bind them all.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Imagebind: One embedding space to bind them all

Reference 24

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Observation 8d28640d-a4de-4356-bbb7-4a48be2761b4 · outbound

This paper cites The llama 3 herd of models.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh The llama 3 herd of models

Reference 25

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Observation 5d7ed6d7-35b3-4a73-b5b5-2abb56757ecd · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 26

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Observation d63d3400-c36f-4480-b124-c841d9bcdf57 · outbound

This paper cites Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following

Reference 27

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Observation 2e1ee376-71a4-4db9-aa63-57741a6a9802 · outbound

This paper cites 3DGen: Triplane Latent Diffusion for Textured Mesh Generation.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh 3DGen: Triplane Latent Diffusion for Textured Mesh Generation

Reference 28

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Observation 197b41c5-4f6c-4d1e-9f6c-239c81a83739 · outbound

This paper cites Audioclip: Extending clip to image, text and audio.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Audioclip: Extending clip to image, text and audio

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:04.181210Z

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Observation 27e6227a-c393-486d-a6ee-25b417887de7 · outbound

This paper cites Y2seq2seq: Cross-modal representation learning for 3d shape and text by joint reconstruction and prediction of view and word sequences.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Y2seq2seq: Cross-modal representation learning for 3d shape and text by joint reconstruction and prediction of view and word sequences

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:04.164581Z

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Observation b4995b3c-6190-4c76-b8ab-69edc51a70df · outbound

This paper cites Shapecaptioner: Generative caption network for 3d shapes by learning a mapping from parts detected in multiple views to sentences.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Shapecaptioner: Generative caption network for 3d shapes by learning a mapping from parts detected in multiple views to sentences

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:04.147643Z

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Observation d63d22a7-1397-408d-b29e-dc4448e15fa6 · outbound

This paper cites Meshtron: High-Fidelity, Artist-Like 3D Mesh Generation at Scale.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Meshtron: High-Fidelity, Artist-Like 3D Mesh Generation at Scale

Reference 32

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Observation 96998ab3-a88e-45a0-b825-219b669877d1 · outbound

This paper cites Training Compute-Optimal Large Language Models.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Training Compute-Optimal Large Language Models

Reference 33

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Observation c6b31e1e-060a-47cf-a5b3-ada16087c02d · outbound

This paper cites 3d-llm: Injecting the 3d world into large language models.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh 3d-llm: Injecting the 3d world into large language models

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:04.130524Z

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Observation 557f4fdb-d06e-474c-bed4-6d5443e43e52 · outbound

This paper cites 2d gaussian splatting for geometrically accurate radiance fields.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh 2d gaussian splatting for geometrically accurate radiance fields

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:04.114018Z

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Observation df367c29-8bab-4ef9-b543-21f3cf8217ce · outbound

This paper cites Shap-E: Generating Conditional 3D Implicit Functions.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Shap-E: Generating Conditional 3D Implicit Functions

Reference 36

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Observation 9d1c6524-b16a-45f7-8236-f802fc02da18 · outbound

This paper cites Scaling Laws for Neural Language Models.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Scaling Laws for Neural Language Models

Reference 37

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Observation 722978e1-1c23-451f-84b0-07a2fa4a87e0 · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh 3d gaussian splatting for real-time radiance field rendering

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T05:46:02.958587Z

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Observation 57656a57-ceec-45be-9ff2-2198c9050bde · outbound

This paper cites Audio-llm: Activating the capabilities of large language models to comprehend audio data.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Audio-llm: Activating the capabilities of large language models to comprehend audio data

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:04.082978Z

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Observation af4325d1-486b-4cd0-beb8-9172f5ee1235 · outbound

This paper cites Acoustic prompt tuning: Empowering large language models with audition capabilities.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Acoustic prompt tuning: Empowering large language models with audition capabilities

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:04.064366Z

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Observation d6a22472-8979-4d7a-9b39-ce398574063f · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Rouge: A package for automatic evaluation of summaries

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:04.045742Z

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Observation b7c04cab-5df4-452b-b907-16e6dea11f07 · outbound

This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 42

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Observation e52ccc30-d723-4289-b6ab-601f3512daba · outbound

This paper cites DeepSeek-V3 Technical Report.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh DeepSeek-V3 Technical Report

Reference 43

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Observation fb0a0720-1010-4989-9d83-12ad3995ab57 · outbound

This paper cites Visual instruction tuning.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Visual instruction tuning

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:04.027881Z

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Observation 57a55a17-f25d-4cf5-b1b1-1a2a7736ae41 · outbound

This paper cites Improved baselines with visual instruction tuning.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Improved baselines with visual instruction tuning

Reference 45

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Observation 69679830-5270-47be-ac1d-c41372bde54c · outbound

This paper cites Music understanding llama: Advancing text-to-music generation with question answering and captioning.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Music understanding llama: Advancing text-to-music generation with question answering and captioning

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:03.991581Z

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Observation c7ea3f5c-fc50-4b8a-9597-c6a4c3943e7d · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Nerf: Representing scenes as neural radiance fields for view synthesis

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T05:46:03.001848Z

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Observation e1b99ffc-6122-4b3c-be17-284b0be69625 · outbound

This paper cites Diffrf: Rendering-guided 3d radiance field diffusion.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Diffrf: Rendering-guided 3d radiance field diffusion

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:03.958899Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e4dd2100-d796-4b7d-a296-398873e4e5f2 · outbound

This paper cites Using an llm to help with code understanding.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Using an llm to help with code understanding

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:03.941472Z

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Observation 7080bd67-099f-406e-9ca3-f99fcc1f7f2a · outbound

This paper cites Polygen: An autoregressive generative model of 3d meshes.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Polygen: An autoregressive generative model of 3d meshes

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:03.924427Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b452c1a1-a7bc-4fbd-9c05-d62f36ce88de · outbound

This paper cites Training language models to follow instructions with human feedback.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Training language models to follow instructions with human feedback

Reference 51

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Observation f652bfdb-4b07-4e19-8a05-127ff6ec6be2 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Bleu: a method for automatic evaluation of machine translation

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:03.896295Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 57cc6acf-8270-46fa-8f43-e3dadb58f3cd · outbound

This paper cites Deepsdf: Learning continuous signed distance functions for shape representation.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Deepsdf: Learning continuous signed distance functions for shape representation

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:03.879027Z

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This paper cites Can large language models understand symbolic graphics programs? In The Thirteenth International Conference on Learning Representations, 2024.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Can large language models understand symbolic graphics programs? In The Thirteenth International Conference on Learning Representations, 2024

Reference 54

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MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Language models are unsupervised multitask learners

Reference 55

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MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Learning transferable visual models from natural language supervision

Reference 56

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MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Improved aesthetic predictor

Reference 57

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This paper cites LLaSM: Large Language and Speech Model.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh LLaSM: Large Language and Speech Model

Reference 58

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MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Meshgpt: Generating triangle meshes with decoder-only transformers

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:03.801014Z

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MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation

Reference 60

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MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Gemini: A Family of Highly Capable Multimodal Models

Reference 61

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MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh LLaMA: Open and Efficient Foundation Language Models

Reference 62

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MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 63

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MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Cider: Consensus-based image description evaluation

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:03.783666Z

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This paper cites LLaMA-Mesh: Unifying 3D Mesh Generation with Language Models.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh LLaMA-Mesh: Unifying 3D Mesh Generation with Language Models

Reference 65

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This paper cites PivotMesh: Generic 3D Mesh Generation via Pivot Vertices Guidance.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh PivotMesh: Generic 3D Mesh Generation via Pivot Vertices Guidance

Reference 66

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This paper cites Scaling Mesh Generation via Compressive Tokenization.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Scaling Mesh Generation via Compressive Tokenization

Reference 67

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This paper cites BLOOM: A 176B-Parameter Open-Access Multilingual Language Model.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Reference 68

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Observation d3bec5d3-a0c0-4b63-9b98-03a66a60cd36 · outbound

This paper cites Chat2svg: Vector graphics generation with large language models and image diffusion models.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Chat2svg: Vector graphics generation with large language models and image diffusion models

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:03.766272Z

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Observation e3af96df-c4c6-4fdb-8580-bdd0fcf9ebb6 · outbound

This paper cites Pointllm: Empowering large language models to understand point clouds.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Pointllm: Empowering large language models to understand point clouds

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:46:03.749012Z

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Observation 80fd669f-fcf6-4cd4-b87f-fc2a25fcd58f · outbound

This paper cites SAMPart3D: Segment Any Part in 3D Objects.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh SAMPart3D: Segment Any Part in 3D Objects

Reference 71

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Observation fff3d07e-f71a-4a78-9f2b-9f95735e183b · outbound

This paper cites ShapeGPT: 3D Shape Generation with A Unified Multi-modal Language Model.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh ShapeGPT: 3D Shape Generation with A Unified Multi-modal Language Model

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-06T05:46:03.126655Z

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This paper cites SpeechGPT: Empowering Large Language Models with Intrinsic Cross-Modal Conversational Abilities.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh SpeechGPT: Empowering Large Language Models with Intrinsic Cross-Modal Conversational Abilities

Reference 73

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Observation dcf63ed2-b0d4-4fbf-ab63-d1f4ad8f5290 · outbound

This paper cites Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-06T05:46:03.136622Z

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Observation 22fb4f3b-fca4-48b9-ad9c-3ae8145b4499 · outbound

This paper cites VGBench: Evaluating Large Language Models on Vector Graphics Understanding and Generation.

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh VGBench: Evaluating Large Language Models on Vector Graphics Understanding and Generation

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-06T05:46:03.142131Z

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